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Table 3 Classifier accuracy with filtering

From: Improving binary classification using filtering based on k-NN proximity graphs

ClassifierGermanBanknote authn.HabermanIonosphereSeismic bumpsWDBC
DT0.7460.9810.7470.8940.9330.931
LR0.760.990.7440.8780.9340.961
NB0.7570.8410.7520.8140.9270.931
SVM0.7610.9990.7360.9290.9340.969
NN0.7470.9790.7420.8630.9340.948
RF0.7430.9920.7480.9220.9340.948
DES-LA0.7680.9960.7470.9280.9340.963